| import os | |
| import json | |
| import random | |
| from typing import List, Dict | |
| from cognition_cocooner import CognitionCocooner | |
| class DreamReweaver: | |
| """ | |
| Reweaves cocooned thoughts into dream-like synthetic narratives or planning prompts. | |
| """ | |
| def __init__(self, cocoon_dir: str = "cocoons"): | |
| self.cocooner = CognitionCocooner(storage_path=cocoon_dir) | |
| self.dream_log = [] | |
| def generate_dream_sequence(self, limit: int = 5) -> List[str]: | |
| dream_sequence = [] | |
| cocoons = self._load_cocoons() | |
| selected = random.sample(cocoons, min(limit, len(cocoons))) | |
| for cocoon in selected: | |
| wrapped = cocoon.get("wrapped") | |
| sequence = self._interpret_cocoon(wrapped, cocoon.get("type")) | |
| self.dream_log.append(sequence) | |
| dream_sequence.append(sequence) | |
| return dream_sequence | |
| def _interpret_cocoon(self, wrapped: str, type_: str) -> str: | |
| if type_ == "prompt": | |
| return f"[DreamPrompt] {wrapped}" | |
| elif type_ == "function": | |
| return f"[DreamFunction] {wrapped}" | |
| elif type_ == "symbolic": | |
| return f"[DreamSymbol] {wrapped}" | |
| elif type_ == "encrypted": | |
| return "[Encrypted Thought Cocoon - Decryption Required]" | |
| else: | |
| return "[Unknown Dream Form]" | |
| def _load_cocoons(self) -> List[Dict]: | |
| cocoons = [] | |
| for file in os.listdir(self.cocooner.storage_path): | |
| if file.endswith(".json"): | |
| path = os.path.join(self.cocooner.storage_path, file) | |
| with open(path, "r") as f: | |
| cocoons.append(json.load(f)) | |
| return cocoons | |
| if __name__ == "__main__": | |
| dr = DreamReweaver() | |
| dreams = dr.generate_dream_sequence() | |
| print("\n".join(dreams)) | |